Towards a sustainable capacity expansion of the Danish biogas sector

Abstract

Promotion of bioenergy production is an important contemporary topic around the world. Vast amounts of research are allocated towards analysing and understanding bioenergy systems, which are by nature multi-faceted. Despite a focus on the deployment of multi-criteria decision-making (MCDM) methods for planning of bioenergy systems, only little research has addressed the location component of bioenergy facility planning. In this paper the authors develop a model for sustainable capacity expansion of the Danish biogas sector allowing for an identification and prioritization of suitable locations for biogas production. The model builds on a framework for spatial planning and decision making through the application of spatial multi-criteria evaluation (SMCE). The paper is structured around a case study including four Danish municipalities in order to demonstrate the power of the spatial multi-criteria evaluation model. The model allows a two level comparison of suitability, within municipalities as well as between municipalities. Criteria weights for generation of alternatives are obtained through an analytical hierarchy process (AHP) analysis, carried out among a group of Danish central governmental decision makers. We find that resource and production economic criteria are given highest priority followed by environmental and social criteria. In all four case study municipalities, the identified alternatives are compared through incorporating economic, environmental and social criteria. It is found that 4–6% of the municipal area is suitable for biogas facility location and among the best performing sustainable locations the potential of reducing overall production costs is 3% as compared with current biogas plants. The results of this paper can provide support to central governmental decision makers, regarding regional allocation of subsidies in the country. Likewise local decision makers can obtain important information for planning and decision support, allowing for a more inclusive and transparent planning procedure.